4 papers
Causal Semantic Alignment for LLM-based Time Series Forecasting
Kexuan Zhang, Xiaobei Zou, Cesare Alippi +2
Recent advances in Large Language Models (LLMs) have opened new possibilities for time series forecasting by enabling alignment between temporal patterns and pretrained word embedd…
DRAN: A Distribution and Relation Adaptive Network for Spatio-temporal Forecasting
Xiaobei Zou, Luolin Xiong, Kexuan Zhang +2
Spatio-temporal forecasting remains challenging under non-stationary environments because both data distributions and spatial relations evolve over time. Temporal normalization and…
Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering
Lu Liu, Yang Tang, Kexuan Zhang +1
Due to the challenge posed by multi-source and heterogeneous data collected from diverse environments, causal relationships among features can exhibit variations influenced by diff…
Caformer: Rethinking Time Series Analysis from Causal Perspective
Kexuan Zhang, Xiaobei Zou, Yang Tang
Time series analysis is a vital task with broad applications in various domains. However, effectively capturing cross-dimension and cross-time dependencies in non-stationary time s…